docs: def export(self, nidm_version, export_dir):
          """
          Create prov entities and activities.
          """
  
          if self.masked_median is None:
              grand_mean_file = self.file.path
              grand_mean_img = nib.load(grand_mean_file)
              grand_mean_data = grand_mean_img.get_data()
              grand_mean_data = np.ndarray.flatten(grand_mean_data)
  
              mask_img = nib.load(self.mask_file)
              mask_data = mask_img.get_data()
              mask_data = np.ndarray.flatten(mask_data)
  
              grand_mean_data_in_mask = grand_mean_data[mask_data > 0]
              self.masked_median = np.median(
                  np.array(grand_mean_data_in_mask, dtype=float))
  
          self.add_attributes((
              (PROV['type'], self.type),
              (PROV['label'], self.label),
              (NIDM_MASKED_MEDIAN, self.masked_median),
              (NIDM_IN_COORDINATE_SPACE, self.coord_space.id))
          )